Data link - https://drive.google.com/file/d/1zV8FDtieAv9H7uN6juSHMZ4RcFiiz9_j/view?usp=sharing

This lab assignment uses the data from the study conducted to investigate the impacts of herbicide exposure on maternal health described in Lab Assignment 1.The analyses that you perform will use data from the tap water consumption group (group 1) and the bottled water consumption group (group 2) separately. The women who consumed only tap water (group 1) are "exposed" because they may have been exposed to the herbicides found in the region's groundwater. Follow the instructions given in Lab Assignment 1. Be sure to appropriately label graph axes. Report any p-values that are less than 0.001 as <0.001 and round numbers reported in your narrative text to 3 decimal places. The positive critical value alone can be reported for two-sided tests. Be sure to appropriately label graph axes.

1.Read the CSV file hgb.csvinto R. Name your data frame hgband re-create the variable change [hgb$change <- (hgb$hgb36-hgb$hgb9)]. A negative value of change should indicate that hemoglobin declined during pregnancy. [Note: No written response is required for this question; include the Rcode that imports your data set and creates changebelow]

1.In this question, the goal is to draw inferences on the true mean change in hemoglobin between week 9 and week 36 of pregnancy in women exposed to herbicides through the drinking of tap water. Our sample from this "exposed" population comes from the pregnant women in the hgbdata set who drankonly tap waterduring pregnancy, i.e., group 1. The before (week 9) and after (week 36) measurements are compared by analyzing their difference, or the change in hemoglobin for each subject.

a.Suppose our research question is to determine whether the average hemoglobin level in the population of pregnant women exposed to herbicides changes significantly during pregnancy.

State the null and alternative hypotheses of this test and perform this test at the = 0.05-level. Report the critical value of this test, and report the test statistic and p-value from your Routput. Also state your statistical conclusion, and your conclusion in the context of the problem.

b.Using your output from part (3a), report the 95% confidence interval for the mean change in hemoglobin in the population of women exposed to herbicides. Does the interval agree with your statistical conclusion in part (3a)? Explain.

c. Suppose we instead hypothesized that exposure to pesticides during pregnancy would significantly lower hemoglobin levels. Remember that a decrease in hemoglobin is reflected by a negative change. State the null and alternative hypotheses of this test and perform this test at the = 0.025-level. Report the critical value of this test, and report the test statistic and p-value from your Routput. Also state your statistical conclusion, and your conclusion in the context of the problem. What is the difference between this test and the test conducted in (3a)?

1.Now we would like to look at the population of pregnant women not exposed to herbicides through drinking water, i.e., group 2, or those women who drank only bottled water during pregnancy.

a.We would like to determine if the average hemoglobin change in pregnant women not exposed to herbicides through drinking water is significantly different from the mean change in pregnant women exposed to mercury. Our sample from this "unexposed" population comes from the women drinking bottled water only in the hgbdata set. Answer this question by conducting the appropriate hypothesis test. State the null and alternative hypotheses of this test and perform this test at the = 0.01-level. Report the critical value of this test, and report the test statistic and p-value from your Routput. Also state your statistical conclusion, and your conclusion in the context of the problem.

b.Report the 99% confidence interval for the mean change in hemoglobin in the population of pregnant women not exposed to herbicides; does the interval agree with your statistical conclusion in part (5a)? Explain.

Only R codes needed. No write up or explanation needed.